OvaCare AI

What it does

My Flutter application, designed for early detection of ovarian cancer subtype classification, leverages the Gemini API to provide a powerful tool for doctors. Ovarian cancer is the fifth leading cause of cancer-related mortality in women worldwide, largely due to late stage diagnosis, given the often vague and inconsistent initial symptoms. Traditional diagnostic methods, reliant on histopathology image analysis by pathologists using microscopic examination, face complexity and inconsistency, leading to moderate agreement among specialists.
This application introduces a histotype-based ovarian cancer subtype classification framework employing multiple instance learning and deep learning algorithms on histopathology images. The approach aims to accurately classify ovarian cancer subtypes, detect outliers, and segment each image into categories of tumor, healthy cell, or dead cell, thus aiding pathologists in diagnostics. Various models were trained to automatically classify hematoxylin and eosin-stained whole slide images and tissue microarrays, yielding promising results.
Ovarall, the flutter application include 2 paths one for doctor and another one for patient with splash screen and onboarding screen. doctor can upload the image then take the results and send it to patient with treatment plan also the application include chat with doctor and patient organized by firebase account to send, get, or clear messages between doctors, and patient with home page for each one.